Three-dimensional numerical investigations of new Austrian tunnelling method (NATM) twin tunnel interactions
Bibliographic record
Abstract
A series of systematic, three-dimensional coupled finite element analyses was carried out to investigate the multiple interactions between large parallel hypothetical twin tunnels constructed in stiff clay using the new Austrian tunnelling method. Special attention was paid to the influence of lagging distance between the twin tunnel excavated faces (LT) and the load-transfer mechanism between the two tunnels. It is found that LT has a stronger influence on the horizontal movement than on the vertical movement of each tunnel, and it significantly affects the shortening of the horizontal diameter of the tunnels. The change of pillar width appears to be an approximately linear function of LT. The location of the maximum settlement is offset from the centerline of the pillar, and the offset increases with a range of LT values. The magnitude of the maximum settlement is independent of LT, however. As LT increases, there is a transfer of load from the lagging (right) tunnel to the leading (left) tunnel, resulting in an increase in the bending moment in the left tunnel but a decrease in the bending moment in the right tunnel. There is a corresponding increase in the axial force at the left springline of the left tunnel and a decrease in the axial force at the right springline of the right tunnel. Due to the twin tunnel interactions, the distributions of pore-water pressures are highly nonsymmetrical at both tunnels.Key words: NATM, tunnel, interaction, three-dimensional, numerical.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".